Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.
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ABSTRACT:
SUBMITTER: Monti RP
PROVIDER: S-EPMC5357637 | biostudies-literature | 2017
REPOSITORIES: biostudies-literature
Publications
Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.
Monti Ricardo P RP Lorenz Romy R Hellyer Peter P Leech Robert R Anagnostopoulos Christoforos C Montana Giovanni G
Frontiers in computational neuroscience 20170320
An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks. In this work, we employ graph embedding algorithms to provide low-dimensional vector representations of networks, thus facil ...[more]
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